Statistical Multiplexing Gain Analysis of Processing Resources in Centralized Radio Access Networks

The next generation of wireless networks faces the challenges of the explosion of mobile data traffic, the associated power consumption, and operation cost. The centralized radio access networks (Centralized RANs) architectures have been proposed to reduce the power consumption and the network operating cost. By integrating many distributed base stations' processing resources in a processing pool and sharing processing resources on demand, the overall required processing resources for the Centralized RAN can be reduced compared to the conventional RAN. This can be measured by the statistical multiplexing gain (SMG). However, most of the SMG analysis only considered the temporal traffic distribution which is not suitable for the current mobile networks. In this paper, we analyze the SMG of processing resources based on a temporal-spatial joint traffic distribution model, which considers the mobile data traffic distribution both in the time and space domains. Based on this model, we derive a formula for the SMG and also a closed-form approximation for that when the spatial traffic distribution is lognormal distribution. The theoretical analysis and simulation results show that the SMG increases with the service threshold ratio P
_th
, but the growth trend of SMG for different area types is not always the same. We also find that the traffic distribution parameters, such as the standard deviation of the lognormal distribution variable's natural logarithm, have a significant influence on the SMG.